World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
17325
World Ranking
4707
National Ranking
188

Kevin Englehart publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Kevin Englehart sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 250 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 560 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 141 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Kevin Englehart D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Kevin Englehart sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering

Overview

Kevin Englehart is affiliated with the University of New Brunswick in Canada. Their research primarily focuses on engineering and neuroscience, with a significant emphasis on biomedical engineering and cognitive neuroscience. They have also contributed to fields related to physical therapy, sports therapy, rehabilitation, cellular and molecular neuroscience, and social psychology.

The main topics of their work include muscle activation and electromyography studies, motor control and adaptation, balance, gait, and falls prevention, as well as advanced sensor and energy harvesting materials. Their research also covers neuroscience and neural engineering, EEG and brain-computer interfaces, and ergonomics and musculoskeletal disorders.

Kevin Englehart has published articles in several scientific venues with a notable presence in the IEEE Transactions on Neural Systems and Rehabilitation Engineering and other journals such as Sensors, Scientific Reports, and bioRxiv (Cold Spring Harbor Laboratory).

  • A Multi-Variate Approach to Predicting Myoelectric Control Usability, 2021, IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • A Multiday Evaluation of Real-Time Intramuscular EMG Usability with ANN, 2020, Sensors
  • Generalizing Upper Limb Force Modeling With Transfer Learning: A Multimodal Approach Using EMG and IMU for New Users and Conditions, 2024, IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • An analytical method reduces noise bias in motor adaptation analysis, 2021, Scientific Reports
  • Cutting through the noise: reducing bias in motor adaptation analysis, 2020, bioRxiv (Cold Spring Harbor Laboratory)

Englehart has collaborated frequently with several coauthors, including Erik Scheme, Daniel Blustein, Ahmed W. Shehata, Erin S. Kuylenstierna, and Jonathon W. Sensinger, each contributing to multiple projects alongside them.

They have been recognized by The Canadian Academy of Engineering, an acknowledgment affiliated with their professional standing in the engineering community.

Best Publications

  • A robust, real-time control scheme for multifunction myoelectric control

    K. Englehart;B. Hudgins

  • Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms.

    Todd A. Kuiken;Guanglin Li;Blair A. Lock;Robert D. Lipschutz

  • Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use.

    Erik Scheme;Kevin Englehart

  • A wavelet-based continuous classification scheme for multifunction myoelectric control

    K. Englehart;B. Hudgin;P.A. Parker

  • Classification of the myoelectric signal using time-frequency based representations

    K Englehart;B Hudgins;P.A Parker;M Stevenson

  • A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses

    Yonghong Huang;K.B. Englehart;B. Hudgins;A.D.C. Chan

  • Myoelectric signal processing for control of powered limb prostheses.

    P. Parker;K. Englehart;B. Hudgins

  • A Comparison of Surface and Intramuscular Myoelectric Signal Classification

    L.J. Hargrove;K. Englehart;B. Hudgins

  • Continuous Locomotion-Mode Identification for Prosthetic Legs Based on Neuromuscular–Mechanical Fusion

    He Huang;Fan Zhang;L. J. Hargrove;Zhi Dou

  • Extracting Simultaneous and Proportional Neural Control Information for Multiple-DOF Prostheses From the Surface Electromyographic Signal

    Ning Jiang;K.B. Englehart;P.A. Parker

  • Resolving the Limb Position Effect in Myoelectric Pattern Recognition

    A. Fougner;E. Scheme;A. D. C. Chan;K. Englehart

  • Continuous myoelectric control for powered prostheses using hidden Markov models

    A.D.C. Chan;K.B. Englehart

  • A training strategy to reduce classification degradation due to electrode displacements in pattern recognition based myoelectric control

    Levi J. Hargrove;Kevin B. Englehart;Bernard Hudgins

  • Simultaneous and Proportional Force Estimation for Multifunction Myoelectric Prostheses Using Mirrored Bilateral Training

    Johnny L G Nielsen;S Holmgaard;Ning Jiang;K B Englehart

  • Principal Components Analysis Preprocessing for Improved Classification Accuracies in Pattern-Recognition-Based Myoelectric Control

    L.J. Hargrove;Guanglin Li;K.B. Englehart;B.S. Hudgins

  • Decoding a new neural-machine interface for control of artificial limbs

    Ping Zhou;Madeleine M. Lowery;Madeleine M. Lowery;Kevin B Englehart;He Huang

  • Multiple Binary Classifications via Linear Discriminant Analysis for Improved Controllability of a Powered Prosthesis

    L.J. Hargrove;E.J. Scheme;K.B. Englehart;B.S. Hudgins

  • Proceedings of the first workshop on Peripheral Machine Interfaces: going beyond traditional surface electromyography

    Claudio Castellini;Panagiotis K. Artemiadis;Michael Wininger;Arash Ajoudani

  • Selective Classification for Improved Robustness of Myoelectric Control Under Nonideal Conditions

    E J Scheme;K B Englehart;B S Hudgins

  • Support Vector Regression for Improved Real-Time, Simultaneous Myoelectric Control

    Ali Ameri;Ernest N. Kamavuako;Erik J. Scheme;Kevin B. Englehart

Frequent Co-Authors

Erik Scheme
Erik Scheme University of New Brunswick
Philip A. Parker
Philip A. Parker University of New Brunswick
Levi J. Hargrove
Levi J. Hargrove Northwestern University
Ning Jiang
Ning Jiang University of Waterloo
Dario Farina
Dario Farina Imperial College London
Todd A. Kuiken
Todd A. Kuiken Northwestern University
Guanglin Li
Guanglin Li Chinese Academy of Sciences
Antonio Bicchi
Antonio Bicchi Italian Institute of Technology
Muhammad Shafique
Muhammad Shafique New York University Abu Dhabi
Strahinja Dosen
Strahinja Dosen Aalborg University

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